2 - 15 vs 50 Year Module: 100% RE by 2050

Comparison case using the functions in CE-MFC to compare 15 year module reliability vs 50 year module reliability.

Folder 15 vs 50 year Module

This scenario is a though experiment comparing a 15-year 95% recyclable module versus a 50-year module 30% recyclable module. This is done to understand potential tradeoffs in PV technology evolution - is it better to create a completely recyclable PV panel, or to extend the module lifetime. This scenario assumes that the 15-year module is 95% recyclable into high quality material, i.e. it will be used to create new modules.

95% recyclability is represented by a 100% collection rate and a 95% efficient recycling process.

The 50-year module uses the previous settings.

Plot the annual waste glass sent to the landfill for this scenario. Here, because the 15-module is 100% collected and only 5% is landfilled during the recycling process the landfilled glass is very low regardless of capacity assumptions. Thus, if the intent is to avoid landfilled material, a 95% recyclable module is the best technology evolution.

Change Reliability Values

Because of the way module lifetime is handled in PV ICE, we need to modify the T50 and T90 values for the Weibull distribution, the economic or project module lifetime, and the degradation rate of the module. This will most accurately and completely represent a module with a particular lifetime.

Change Recyclability Values

Create the range of values that recycling and lifetime can hold

Turn IRENA lifetime values on or off & run PV ICE simulation

Modifying Installed Capacity requirements to match 30 Year Module

Maintaining installed capacity, i.e. the ability to generate electricity is of paramount importance. Therefore, we want to examine how many more modules need to be deployed if they only last 15 years.

This is accomplished by first creating the scenario in our simulation, and calculating the mass flow as before. Then, the difference between the installed capacity of the 30 year module and the installed capacity of the 15 year module is taken for each year. This difference generates a new annual deployment projection where additional modules are deployed to compensate and capacity of the 15 year module = capacity of the 30 year module. Then calculate mass flow is run for the scenario with the new annual deployment projection, allowing us to track the extra material needed.

Modifing the installed capacity requiremetns according to t50.

Needs to run each year becuase it needs to calculate the acumulated installs and deads.

And create a 50 year decreased installs by the same principle

Plots

Same plots but not automatic from the software to control more the parameters

Calculating Overall changes between the Scenarios

Normalize by Base Scenario

Separate out the 95% RE projection from the 57% to normalize by the correct projection

Cumulative results by material

Output Data for Charting

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Full Variation of Lifetime and Recycling

To explore the full range of lifetime vs recycling, we decided to make a 2d plot varying lifetime on one axis, and recycling on the other. This section uses only the 95% RE scenario, and maintains capacity of the 30 year deployed module projeciton (i.e. compensates for shorter and longer lived modules). Everything will be normalized to the 30 year module at the end of the calculations.

Create PV ICE defaults scenario with 95% RE

Create t50 and t90 values to match the range of module lifetimes

In PV ICE we assume that 90% of the modules should be reliabile enough to meet the economic project lifetime. Therefore, the t50 and t90 values need to be modified for each lifetime in the range.

Create the lifetime and recycling combinatorics simulations

Cumulative Comparison

Calculate the comparison of cumulative differences in material demands, wastes, and installed capacity as a relative to the PV ICE default values.

Make bar chart of cumulative capacity in 2050

Installation compensation

Cumulatives with Installation Compensation